Evaluation of Inherited Resistance Genes of Bacterial Leaf Blight,Blast and Drought Tolerance in Improved Rice Lines

Ibrahim Silas AKOS ,Mohd Y.RAFII ,Mohd Razi ISMAIL ,Shairul Izan RAMLEE,Noraziyah Abd Aziz SHAMSUDIN,Asfaliza RAMLI,Samuel Chibuike CHUKWUSenesie SWARAY,Momodu JALLOH

(1Laboratory of Climate-Smart Food Crop Production,Institute of Tropical Agriculture and Food Security,Universiti Putra Malaysia,Serdang 43400,Selangor,Malaysia;2Department of Crop Science,Faculty of Agriculture,Kaduna State University,801 Kafanchan,Kaduna 801139,Nigeria;3Department of Crop Science,Faculty of Agriculture,Universiti Putra Malaysia,Serdang 43400,Selangor,Malaysia;4School of Environmental and Natural Resource Sciences,Faculty of Science and Technology,Universiti Kebangsaan Malaysia,Bangi 43600,Selangor,Malaysia;5Rice Research Centre,Malaysian Agricultural Research and Development Institute,Serdang 43400,Selangor,Malaysia)

Abstract:Improved rice lines were developed frome three parents with the resistance or tolerance to bacterial leaf blight,blast and drought stress,respectively,using single-,double- and three-way crosses.The improved lines were assessed for agro-morphological and yield traits under non-drought stress(NS)and reproductive-stage drought stress(RS)treatments.The mean comparison of traits measured between parent plants and progenies(improved lines)were similar,and there were significant and non-significant differences among the parents and improved lines(genotypes)under NS and RS.Smilarly,there was significant and non-significant differences in the interaction among both parent varieties and improved lines for NS and RS.Cluster and 3D-model of principal component analysis did not generate categorical clusters according to crossing methods,and there were no exclusive crossing method inclined variations under the treatments.The improved lines were high-yielding,disease resistant,and drought-tolerant compared with their parents.All the crossing methods were good for this crop improvement program without preference to any,despite the number of genes introgressed.

Ke y words:rice;bacteria leaf blight;blast;drought tolerance;resistance gene

Rice is a cereal crop of the grass family gramineae.It thrives in both lowland and upland environments(Latif et al,2011),and provides 76% calorie intake of mostly the Southeast Asian population and 21% food need(Luo et al,1998;Fitzgerald et al,2008;Miura et al,2011).The consumption ratio makes it a high demand food crop,with an approximate production ratio expected to be up by 40% of present global production to meet the need of the world’s increasing population by 2030(Khush,2005).

The high demand for rice necessitates measures to ensure sustainable high yield production since it is culpable of attack by biotic and abiotic stress of bacteria leaf blight(BLB),blast and drought.These conditions of BLB and blast have caused significant yield loss to farmers depending on the disease incidences with recorded 1%-50% and 100%(Zhai and Zhu,1999;Jia et al,2000;Asghar et al,2007;Ashkani et al,2011;Zhang et al,2015),while drought stress could also result in significantly low rice yield or even 100% depending on the stage and duration of water deficit(Shamsudin et al,2016;Akos et al,2019b).

Cultivation of resistant and tolerant rice variety to BLB,blast and drought presents a better approach than chemical spray of fungicide and insecticide due to their environmental effect on other important fauna and flora(Ribot et al,2008),and therefore,minimizes loss of yield.The development of multiple varieties with a durable broad spectrum of resistance or tolerance proffers a better way of combating stresses(Kumar et al,2014;Sundaram et al,2014).About 40 BLB resistance genes(Natrajkumar et al,2012),101 blast resistance genes and 350 QTLs have been identified(Rajashekara et al,2014).

Agro-morphological and yield parameters,which were frequently used to evaluate the yield potential of grain crops,were applied in this study to evaluate improved rice lines with resistance and tolerance genes/QTLs for BLB,blast and drought.These parameters included days to 50% flowering(DTF),plant height(PH),panicle length(PL),number of effective tillers(ET),total number of tillers(TT),number of fully filled grains per panicle(FFG),100-grain weight(HGW),grain length/width ratio(GLWR)and growth duration(GD).Meanwhile,PL,ET,GLWR and HGW are valuable agronomic traits correlating with high-yielding potential,and they are quantitative trait and are influenced by the environmental factors(Han et al,2006;IRRI,2014;Chang et al,2016;Taglea et al,2016;Akos et al,2019a).The objectives of this study were to determine the yield potential of the improved lines with multiple traits of disease resistance and drought toleranceand to evaluate the influence of crossing methods on yield potentials of improved rice lines developed through marker-assisted pedigree selection.

RESULTS

Development and selection of improved lines

Among all the lines,only 11 lines contained the resistance/tolerance genes(Table 1 and Fig.S1),responding well in resistance/tolerance(phenotyping)to disease pathogens and water deficit stress,and they were homozygotes to the recipient parent.With the most virulent strains of the pathogens ofX.oryzaeandM.griseaand water stress test,the selected improved lines were resistant(R),moderately resistant(MR)and tolerant,except for the susceptible(non-resistant)varieties used as control which were highly infected(Fig.S2).

Evaluation of agronomic traits of improved lines

The agro-morphological and yield parameters of the new improved rice lines were observed and measured to ascertain the differences between the various rice genotypes and the parent plants.Analysis of variance(ANOVA)showed that genotypes had a significant difference,except in ET and GD.DTF and PL were significantly different,while difference in PH,TT,FFG,HGW and GLWR were highly significant.No significant differences were recorded in all the morphological traits under non-drought stress(NS).Phenotyping for drought tolerance was carried out to determine the level of improved lines’ tolerance to reproductive-stage drought stress(RS).ANOVA showed a highly significant difference among genotypes on DTF,PL,FFG and GD parameters,while there were no significant differences among the replicates(TableS1).This clearly indicated the effect of drought on these very important yield-related parameters.The mean separation clearly indicated significant differences between the control plants and the selected improved lines(Table 2).

Table 1.Genotyping of 11 improved lines with resistance to blast and bacteria leaf blight(BLB)and tolerance to drought.

Table 2 shows nine traits under three treatments.There were 14 lines under NS,and 10 lines under RS and pool.Nine improved lines comprised of blast and drought toleranceqDTYor BLB resistance genes,with a susceptible variety IRBB60 as control,and two single crossed lines PB12 and PB15 had no drought tolerance QTLs.Basically,only lines that had drought tolerance QTLs introgressed were treated for RS.The improved lines,except PBD3,showed highest means on PH under pool treatment,followed by RS and NS.The lines DPB7,DPB13 and DPB20 had higher FFG,HGW and GLWR under RS and pool than NS.DPB12 had highest GLWR under RS,followed by pool and NS.For the three treatments,means of the improved lines under pool was higher than RS.DTF and GD of the improved lines showed the highest means under RS,followed by pool and NS.

Furthermore,lines showed the highest and lowest DTF as 89.0 and 86.0 d under NS,and as 96.0 and 91.8 d under RS.The lowest and highest PH were 102.3 and 112.3 cm under NS,while 96.3 and 102.1 cm under RS.The lowest and highest of PL for NS was 22.86 and 26.5 cm under NS,while 22.6 and 24.1 cm under RS.Lines showed the highest and lowest PL of 26.58 and 22.86 cm under NS and 24.10 and 20.68 cm under RS,respectively.But there was an exceptional difference between the line PBD3,which showed that 23.2 cm in PL under RS whereas 22.86 cm under NS,showing no effect of RS on PL.FFG was the lowest as 152.2 and the highest as 178.4 under NS,while 43.8 and 59.4 under RS.The lowest and highest HGW were 2.47 and 2.63 g under NS,while 2.32 and 2.43 g under RS.GLWRs of DPB7,DPB12,DPB13 and DPB20 under RS were higher than those under NS.ET and TT of the improved lines showed no differences between the two treatments.

Under NS treatment,DTF of Putra-1 was 89.0 d.with no significant difference from other improved lines except PD14,DPB7,DPB12 and DPB20(Table 2).For PL,PBD3(the lowest)and DPB20(the highest)differed from the other improved lines.All other parameters showed no difference between parent plant(Putra-1)and progenies,except the parameters of ET(DPB12),FFG(PD15,PDB3,DPB12 and DPB13),HGW(PB12,PD14,PBD1,DPB13 and DPB20),GLWR(PDB3,DPB13 and DPB20).These improved lines were not similar to Putra-1,but similar to either of the two donor parental plants of IRBB60 and MR219-PL-137.Under RS,the improved lines were different from the susceptible variety IRBB60 because of introgressed drought tolerance QTLs(qDTY)(Table 2).

Heritability estimate on NS and RS treatments and pool

The broad sense heritability of characters under NS and RS treatments ranged from 20.22% to 88.13%(Table 2).These results indicated environmental factors also influenced the magnitude of heritability.Moderate heritability was lesser environmentally influenced while higher heritability was not environmentally influenced.

Under NS,all characters showed higher heritability(66.27%-85.92%),which suggests no environmental influence,except on PH,PL and GD(28.63%,31.13%and 39.77%,respectively).Under RS,the characters were medium or high except PH(low heritability of 20.22%).The heritability of pool was all low ranged,which clearly indicated influence of environmental factors.

There were interactions between RS treatment and genotypes(Table S2).DTF,PL,FFG,GLWR and GD interacted at highly significant level,and TT and HGW interaction were significant,while the other parameter interactions were not significant.The significant interactions were because of the variation in treatments among the genotypes,comprised of data from the improved lines(progenies)subjected to RS and NS conditions.

Cluster analysis for NS and RS

An important criterion for selecting parental plants in genetic variability analysis is the estimate of the extent of variation among the genotypes.The 14 genotypes were divided into 11 groups under NS based on their morphological traits at genetic dissimilarity of 2.39(Fig.1-A).Groups II,VII and VIII had two genotypes each,while all the others had single genotype.Whereas,under RS,the 10 improved lines and a control variety were divided into 7 groups at genetic dissimilarity of 2.60(Fig.1-B).Group III had three genotypes(PDB3,DPB13 and DPB20),while group II had two genotypes(PD14 and PBD3).Groups I,IV,V,VI and VII showed only a single genotype in each

group.Principal component analysis(PCA)showed that PBD3,DPB20,IRBB60,DPB12,DPB7 and MR219-PLs were the farthest from the centroid,and DPB13,Putra-1,PBD1 and PDB3 were intermediate between the centroid and those farthest from the centroid,while PB12,PB15,PD14 and PD15 were the closest to the centroid(Fig.1-C).Under RS,the genotypes were also categorically divided into three groups based on their distribution on the 3D model.DPB12,PBD3,DPB20 and PDB3 were the closest,and PD14 was intermediate,while PD15,DPB7,DPB12 and PBD1 were the farthest(Fig.1-D).

Estimate of correlation coefficient relationship among NS,RS and pool

The correlation coefficient relationship of the nine morphological and yield traits showed that there were no significant correlation relationships under NS,RS and pool treatments between ET and DTF,TT and DTF(Table 3).Between ET and PH,TT and PH,no significant correlation was found either,likewise between ET and PL,GLWR and PL,FFG and TT,HGW and TT,GLW and TT,GD and TT,and between HGW and GLWR.Meanwhile,positively linear and highly correlated relationship was observed between TT and ET under NS,RS and pool.Every other parameter was either positive or negatively correlated with low,moderate or high linear relationships.

Table 2.Traits of genotypes under reproductive-stage drought stress(RS),non-stress(NS)treatments and pool.

Analysis of crossing methods

Three crossing methods [single cross,double cross and three-way(reciprocal)cross] were used to develop the improved lines(Table S3).The results of mean comparison showed little variations between some genotypes and their recipient and donor parents.PH showed DPB7 and DPB20,three-way reciprocal cross genotypes,different from their parent plants(recipient and donors),but similar to other genotypes of same and different crossing method.PL showed variation from the parents on a double cross PDB3 only,yet similar to other genotypes of other crosses.HGW had two genotypes PBD1 and DPB13 which were developed from three-way crosses but the later was from the reciprocal cross.FFG,GL and GLWR had variation in means between the parents and progenies,but no variation among the improved lines,including PDB3 and DPB13 which are double cross and three-way reciprocal cross respectively.

Fig.1.Clusting analysis of 14 rice genotypes using morphological and yield traits and principal component analysis(PCA).

Table 3.Correlation coefficients of nine traits under non-stress(NS),reproductive-stage drought stress(RS)and pool.

3D-model of PCA showed that under NS,two single cross genotypes PB15 and PD14 were closest to the centroid,while under RS the single crossed genotype PD14 was intermediate,and PD15 was the farthest.These non-separated alone progenies from other cross methods were also distributed across the three divisions of centroid,intermediate and farthest from the centroid.

There were no definite variations among the three different cross methods both on mean comparison and PCA,with only some random differences.These differences cannot be substantially termed to be variation according to the crossing method.

DISCUSSION

The development process of improved lines followed a systematic marker-assisted pedigree breeding approach because all the parent cultivars were high-yielding with their unique trait of resistance and tolerance.Evaluation of agronomic traits of improved lines often requires that the genes of interest have been introgressed and marker-assisted selection is applied.It is also obligatory on the plant breeder to challenge the improved material with strains of requisite disease pathogens or stress condition,which should agree by expressing the desired or expected condition of either resistance or tolerance.Evaluation under normal and stressful conditions gives a good assessment of the plant materials.This research evaluated lines developed for resistance to BLB,blast,and tolerance to drought.Miah et al(2016)evaluated improved rice lines developed with resistance to blast after genotyping and phenotyping,while Shamsudin et al(2016)evaluated drought tolerance under RS after genotyping of drought tolerance QTLs.

Significant differences on ANOVA for both NS and RS were due to conditions of non-improved lines(parent plants),which formed part of the lines analyzed.In the case of NS,there were three parent plant varieties with different traits and yield values,while drought tolerant lines were subjected to RS along with non-drought tolerant variety.The yield values will vary and create differences.

Parameters under NS and RS showed statistically significant differences and similarities.Although most of the improved lines under NS were similar to either the recipient parents or any of the donor parents,the RS were not similar with the control,a susceptible variety because it had no trait of tolerance to drought and therefore could not produce much resistance for comparison with the improved drought tolerant line.Water deficit stress affects these quantitative traits,which was also confirmed in this study(Garrity and O’Toole,1994;Latiffe et al,2004;Atlin et al,2006;Barnabas et al,2008).There was alternating variation among parameters,especially ET and TT.This was because the treatment for drought was at the reproductive stage when the tillers were matured and could not be affected by water deficit stress of just about two weeks.Record has shown that drought affects tillers at vegetative stage(Cruz et al,1986).

h2Bis the total ratio of genetic variance to phenotypic variance.In other words,the proportion of the parental gene inherited in the progenies is influenced by the environment and expressed in the phenotypic traits.h2Bis expressed as low,medium and high represented as 0-30%,30%-60% and ≥ 60%,respectively.The level of heritability was basically environmentally influenced due to the peculiarity of the requirement of rice plants.Climatic factors present a great challenge to rice plant.There are various optimum temperature requirements for various growth phases and stages,and temperature deviations have effect on that phase of development(Tashiro and Wardlaw,1989;Baker and Allen,1993;Singh et al,1996).Incidentally,the result indicated that environmental factors had only little influence on heritability of yield maturity.All ranges of heritability percentage estimates were also reported by Oladosu et al(2014),Meena et al(2016)and Ridzuan et al(2019).The low heritability may not present the inherited genes’ true nature because controlled environment of research may present a variation when in a field environment.

Significant levels of interactions among the NS and RS traits were basically due to treatment conditions that would normally impact the agro-morphological and yield parameters.Shortage of water was responsible because of its importance to living cell functioning and turgidity(Sukhla,2012).The parameters affected are yield borne especially FFG.DTF,GD,FFG and PL are affected by drought stress(Juraimi et al,2009;Sikuku et al,2009;Mashitah,2018).Variation of the major yield component was also attributed to the biochemical,physiological,morphological and anatomical effect of water deficit condition(Serraj et al,2009).The reproductive stage of rice is highly watersensitive,and drought stress affects flowering and heading(Davatgar et al,2009).Drought stress often results in low tissue water potential rice(Sikuku et al,2010).Generally,low yield underscores the importance of water(Juraimi et al,2009).

Specific information on the degree and nature of genetic variability is important for selecting the ideal parent plant,thereby making the required crosses low(Guerra et al,1999;Yatung et al,2014).PCA often confirms the effectiveness of cluster analysis,which shows the length,width and height of the PCA,and the distribution of the genotypes.Those genotype distanced away from the centroid were considered to be genetically diverse and were better off compared to those closer.Cluster analysis and 3D model give genetic variability of the lines with low,medium and high levels of variabilities,which was shown on the closest to the centroid,those intermediate the centroid and farthest to the centroid,respectively.

While the correlation coefficient was varying in relationship with each parameter according to Pearson’s correlation coefficient,r-value helps to identify the association between two unique traits,even though it cannot measure the magnitude(extent)of association gives a clue as to the relationship.The interpretation of correlation coefficient was given,but Ratner(2009)provides an accepted standard guideline.Ther-value could indicate no linear relationship,positive linear relationship and negative linear relationship,represented by 0,+1 and -1,respectively.Low,moderate and strong positive linear relationships are represented with values ranging from 0-0.3,0.3-0.7 and 0.7-1.0,respectively while 0 to -0.3,-0.3 to -0.7,and -0.7 to-1.0 would indicate as low,moderate and strong negative linear relationship,respectively.

The rice lines developed by single,double and threeway crosses,which agreed with each other genotypically and phenotypically,were not significantly different from either recipient or donor parents on morphological and yield traits under NS treatment.However,under RS treatment,there was difference between the susceptible parents and improved lines for a significant number of morphological and yield traits,but not among the genotypes(improved lines).The yield value in NS treatment was not significantly different between the parent plants and the RS.There were no crossing methods,whether single,double or three-way(reciprocal)that posed any morphological and yield advantage over another.Even on PCA,the genotype variations were not exclusively cross method inclined.Therefore,the crossing methods were all good for those crop improvement programs due to limited parents in this study.

METHODS

Plant materials and breeding design

New improved lines were developed by three parent cultivars(Putra-1,P;IRBB60,B;and MR219-PL-137,D)through the pedigree breeding method,with multiple resistances to BLB and blast and tolerance to drought,respectively(Table S3).Two F1s(PD and PB)were developed and confirmed genotypically with the double bands as donors,respectively.The third varieties of IRBB60 or MR219-PL-137 were introgressed into the F1s(PD and PB)to produce PDB(PD × B)and PBD(PB × D)by the three-way cross.DPB was developed by the three-way reciprocal cross with F1(PB)as the donor parent and MR219-PL-137(D)as the recipient,and the F1progenies maintained as single crosses.These were still considered F1as double- and three-way crosses(Table S4).

Improved rice lines were developed from three parents,bacteria leaf blight(BLB)resistant variety IRBB60,which had four BLB resistant genes(Xa4,xa5,xa13andXa21),blast resistant variety Putra-1,a Malaysia commercial high-yielding rice variety with three blast resistant genes(Pi,Pi9andPiz),and a drought-tolerant pyramided line(MR219-PL-137)with three drought tolerance QTLs(qDTY2.2,qDTY3.2andqDTY12.1).The improved lines were developed through single-,doubleand three-way crosses through the marker-assisted selection method.These new lines were developed in a glass house at Rice Research Centre and Laboratory of Climate and Smart-Food Crop Production,Universiti Putra Malaysia,Malaysia.

Assessment of resistances and tolerance of improved lines

These new lines were both genotypically and phenotypically confirmed to carry and express the genes/QTLs for resistance toXanthomonas oryzaepvoryzaeandMagnaporthe grisea,and for tolerance to drought stress(Table S4)according to IRRI(2014)with some modifications.The strains of the virulent pathotypes P7.2 used to challenge the plants were obtained from Malaysia Agricultural and Research Development Institute,Malaysia,while severe drought stress was imposed at the reproductive stage for more than two weeks with U-shaped to rolled-shaped leaves,dried soil and depth of over 15 cm(pots)dried using soil moisture meter.

Experimental layout and cultivation

The experiment was set out in a glass house at Rice Research Centre,Universiti Putra Malaysia,with three plants each per pot and labeled accordingly.The leaves of the parents and their progenies were collected and genotyped by gel electrophoresis analysis after DNA extraction,nanodrop spectrophotometry and PCR amplification,to ascertain the stability of the progenies as a non-segregating generation.The non-segregating(pure-lines)and parent plants were the lines laid in rows according to their genotypes.

Data collection

Nine quantitative traits were collected and measured from the three parents and their progenies(improved lines)under non-drought stress(NS)and reproductive-stage drought stress(RS)at about 120 d after seed sowing in two planting seasons(2019-2020),and each genotype replicated five times.The traits measured included DTF,PH,PL,ET,TT,FFG,HGW,GLWR and GD.

Statistical analysis

The evaluated data were subjected to analysis of variance(ANOVA)using Statistical Analysis Software(SAS)version 9.4.The results were expressed in mean,correlation coefficient and the least significant difference to set the relationship among the parameters.To determine the genetic variability based on the nine quantitative traits,cluster analysis was employed.The genetic relationship among the parent varieties and improved rice lines was determined in conformity with Unweighted-Pair Group Method using Arithmetic Average(UPGMA)algorithm,and Sequential,Agglomerative,Hierarchic and Non-overlapping method using Numerical Taxonomy Multivariate Analysis System,Exeter Software,Setauket,NY,USA software(NTSYS v2.1).

ACKNOWLEDGEMENTS

This study was supported by the Higher Institution Centre of Excellence(HiCoE)Research Grant(Grant No.6369105)and the Translation Research Grant Padi Putra:Accelerating Rice Food Security and Socio-Economics for Rice Farming Communities,Ministry of Higher Education,Malaysia.

SUPPLEMENTAL DATA

The following materials are available in the online version of this article at http://www.sciencedirect.com/journal/rice-science;http:// www.ricescience.org.

Fig.S1.Homozygous stable gel score of five populations using the three crossing methods.

Fig.S2.Phenotyping after inoculation.

Table S1.ANOVA for 14 and 10 parental and progeny lines under non-stress and reproductive-stage drought stress treatment.

Table S2.ANOVA for 10 progeny lines between reproductivestage drought stress treatment and genotypes.

Table S3.Methods of crossing for development of improved lines.

Table S4.Polymorphic,linked and flanking markers of resistance genes and drought tolerance QTLs.